With advances in various technologies, wearable sensing devices or systems are increasingly popular. A wearable sensing system may need to be comfortably attached to the human body, and may be able to measure and quantify various parameters of a user's physiological context, such as, for example, electrocardiogram (ECG), electromyogram (EMG), electroencephalogram (EEG), and the like, as well as provide user authentication based on biometric measurements, to enable “no password” device unlocking. However, the quality of a user's physiological context readings and performance of biometric authentication algorithms (e.g., based on ECG readings) are highly dependent on the quality and repeatability of signals (e.g., ECG signals) sensed from the human body. The quality of ECG signals is dependent on the electrode material and the electrode-tissue impedance (ETI). ETI levels may vary dependent on the level of dryness of the hands of the user. This difference in ETI may affect the quality and repeatability of ECG signals and in turn, the accuracy of measurements of the user's physiological context and biometric authentication.